308 results about "Soil mass" patented technology

The invention discloses a large-diameter shield tunneling parameter optimization method and system based on digital twinning, and relates to the technical field of shield tunnel numerical simulation, machine learning and digital twinning, and the method comprises the steps: obtaining shield tunnel construction site data, and constructing a virtual digital twinning body; building a training sample set based on virtual numerical twinborn generation data; training an agent model by using the training sample set; during construction, actual stratum response data and tunneling parameter data are obtained in real time, the real-time data are input into the soil mass parameter inversion agent model, and the optimal value of the soil mass parameter is rapidly output; the optimal value is input into the virtual digital twin, and dynamic real-time updating of numerical simulation is carried out; and on the basis of the updated soil parameter data and the tunneling parameter data in the next construction step, stratum response prediction data are obtained through the stratum response prediction agent model, so that the tunneling parameter data are adjusted and optimized. According to the invention, more accurate numerical simulation and safe and efficient tunneling of the shield tunnel can be realized.

The invention discloses a dangerous rock falling motion feature prediction method based on multi-source data fusion, and belongs to the technical field of engineering geology. Comprising the steps of collecting dangerous rock multi-source data to construct a basic information base; processing dangerous rock multi-source data based on a CNN algorithm, identifying a dangerous rock contour and calculating geometric features; the dangerous rock multi-source data is processed through multiple algorithms, and the terrain is reconstructed to generate a digital elevation and terrain model; analyzing a vibration signal frequency spectrum, quantifying dangerous rock multi-source data features and determining a fusion weight; fusing the multi-source data of the dangerous rock to construct a three-dimensional real scene model and construct a physical and mechanical model; establishing a historical database, selecting a machine learning algorithm to construct a data driving model, and adopting an optimization algorithm to predict a rockfall movement track and state; and determining a two-dimensional simulation key section, establishing a two-dimensional numerical model, and dynamically simulating and calculating rockfall movement and rock-soil body response. According to the scheme, the defects in the aspects of dangerous rock falling motion feature prediction and protection design in the prior art are overcome, and the prediction accuracy and efficiency are improved.

The invention discloses a weak intercalated layer control-based closed conduit-slope system optimization layout method, which comprises the following steps of S1, geological survey and parameter acquisition: accurately positioning a weak intercalated layer through a geological radar and drilling coring, and determining a rock-soil body strength parameter by combining a laboratory rock-soil mechanical test, geological radar data and rock-soil body strength parameters are analyzed through a random forest algorithm, and the interlayer space distribution rule is predicted. By combining geological survey, numerical simulation, intelligent optimization and dynamic monitoring technologies, scientific layout and adjustment of a closed conduit-side slope system are realized, a weak intercalated layer seepage path is accurately cut off, the safety coefficient of the side slope is effectively improved, meanwhile, expansion of a plastic zone is effectively inhibited, settlement of an overlying soil body or large-range deformation of the side slope is reduced, and the stability of the side slope is improved. The seepage stability and the stress slow release capacity of the system are enhanced, the safety of the water diversion project in a complex geological area is improved, and an operable technical path and basis can be provided for layout of similar projects in the future.

The invention discloses an embankment hidden danger detection and early warning method and system based on electric field and electromagnetic field coupling, and the method comprises the following steps: obtaining and processing the resistivity and dielectric constant of an embankment dam body, constructing a joint inversion objective function based on a processing result, and carrying out the detection and early warning of the embankment hidden danger. A joint inversion model is established, a minimum joint inversion objective function is used for solving, a multi-physics field joint inversion result is obtained and used for delineating an abnormal area, a time-shifting resistivity monitoring network is arranged in the area for detection, the seepage velocity is obtained, soil mass mechanical parameters are defined, and the seepage velocity is calculated. And constructing an embankment hidden danger numerical model, using seepage velocities as boundary condition input, simulating embankment dam body stability safety coefficients under different seepage velocities, setting an early warning threshold value, and giving an alarm when the embankment dam body stability safety coefficients reach the early warning threshold value. Through coupling analysis of the earth electric field, the seepage velocity and the like, data multiplicity is effectively eliminated, the defect resolution is remarkably improved, and the misjudgment risk is greatly reduced.

The invention relates to the technical field of earthwork compaction, and discloses a pipe ditch backfilling and tamping system based on excavator modification. The system comprises an earthwork condition dynamic sensing module which captures a bucket tooth track, a hydraulic oil cylinder pressure pulse and a soil mass vibration spectrum in real time and combines a historical database to construct a model to output a theoretical compaction degree curve; a multi-source compaction difference analysis module performs three-dimensional deviation detection on the theoretical curve and the actual settlement volume data to generate a construction grid-level compaction difference tensor; the defect area association mapping module inputs the tensor into a geological topology analysis network, generates a loose defect propagation path probability cloud chart by combining soil parameters and identifies weak sections; and the tamping strategy self-adaptive configuration module automatically sets operation parameters according to the cloud picture, activates high-precision monitoring on a high-probability defect section, and applies a dynamic excitation force test on adjacent grids, so that intelligent management and control of the backfilling and compacting process are realized.

The invention discloses a rapid reconstruction method, device and equipment for a soil mass freeze-thaw hydrothermal field and a storage medium, and the method comprises the steps: building a one-dimensional soil column frost heaving-thaw collapse calculation model through finite element software, carrying out the simulation calculation to obtain a soil mass one-dimensional freeze-thaw transient temperature field and a moisture field, and obtaining a source domain data set containing the position, time, temperature and saturation; the position and time in the source domain data set serve as input, temperature and saturation serve as output, a deep neural network is established, and a loss function comprises data loss and physical loss and also relates to a temperature field and a moisture field; training the source task model to obtain neural network parameters; and training the target task model. On the basis of numerical simulation and deep transfer learning, the problem of multi-field coupling under the background of machine learning is solved, and meanwhile, the generalization performance of the model is improved, so that rapid reconstruction of the transient temperature field and the moisture field of the one-dimensional frost heaving-thaw collapse test of the soil body under the condition of sparse measuring points is realized.

The invention discloses an expansive soil free expansion rate and permeability coefficient field test device and method, relates to the technical field of expansive soil tests, and aims to solve the problems that in the prior art, expansive soil expansion potential judgment standards are not unified, and test data discreteness is large. Comprising a cutting ring assembly, a moisture content measuring assembly, a displacement measuring assembly and a water supply assembly. The cutting ring assembly is used for fixing a test soil body; the moisture content measuring assembly monitors the moisture content of the soil body in real time; the displacement measuring assembly records soil surface and deep displacement; the water supply assembly controls water injection. The test method comprises a test method and a numerical analysis method, the permeability coefficient and the free expansion rate of the soil body are calculated by injecting water and monitoring the moisture content and the displacement change of the test soil body, a moisture content curve is fitted by combining numerical analysis, the expansion coefficient and the saturated moisture content are solved, and the free expansion rate of the soil body is finally determined. The free expansion rate and the permeability coefficient of the expansive soil are rapidly and accurately measured on site, the expansion potential is judged, and a reliable basis is provided for engineering application.

A true triaxial rock-soil mass test device and a test method therefor, the test device comprising a triaxial loading module, wherein the triaxial loading module comprises a triaxial servo loading system and a triaxial bearing system, the triaxial servo loading system being configured to apply an X-direction pressure, an Y-direction pressure and a Z-direction pressure to the triaxial bearing system; a grouting module, wherein the grouting module is connected to a grouting fracturing pipe (13) in the triaxial bearing system by means of a pipeline; a hydraulic cracking module, wherein the hydraulic cracking module is connected to the grouting fracturing pipe (13) in the triaxial bearing system by means of a pipeline; and a data acquisition and analysis module, wherein the data acquisition and analysis module is connected to an ultrasonic transmitting sensor and an ultrasonic receiving sensor in the triaxial bearing system by means of a line. With the test method using the test device, triaxial grouting tests and triaxial hydraulic cracking tests can be performed, a true triaxial hydraulic cracking and grouting test on a complete rock mass can be performed, and a true triaxial grouting test on a loose mass can also be performed.

The invention relates to the technical field of mine engineering, and discloses a mine geotechnical engineering monitoring and evaluation emergency feedback system and method.The mine geotechnical engineering monitoring and evaluation emergency feedback system comprises a data acquisition module, a data processing module, a risk assessment module, an emergency feedback module and a user interaction module; the temperature, humidity, stress, displacement and other parameters of the underground rock-soil body of the mine can be collected in real time, and the collected data are transmitted to the data processing module through a wireless network; the data processing module processes and analyzes the collected data through a data fusion algorithm; the risk assessment module dynamically assesses the stability of the rock-soil body based on the real-time monitoring data; and the emergency feedback module automatically generates an emergency response scheme according to the evaluation result and notifies related personnel. According to the method, the safety of mine engineering can be remarkably improved, potential risks are reduced, the life safety of mine operators is guaranteed, the accident occurrence probability is reduced, and smooth production and operation of mines are guaranteed.

The invention discloses a shield tail sealing failure intelligent judgment method and device. The method comprises the steps that gap data of a duct piece and a tail shield, external soil mass pressure data and grease state data are obtained; inputting the gap data into a shield attitude abnormity early warning model, and outputting a first prediction result; inputting the external soil body pressure data into an external soil body abnormity early warning model, and outputting a second prediction result; the external soil body abnormity early warning model is used for determining an external soil body pressure sudden change turning point; inputting the grease state data into a grease abnormity early warning model, and outputting a third prediction result; the grease abnormity early warning model is used for determining whether the grease contains water, whether the grease temperature is abnormal and whether the grease pressure is abnormal according to the grease state data; and based on a Bayesian algorithm, carrying out fusion processing on the first prediction result, the second prediction result and the third prediction result, and outputting a comprehensive prediction result. The early warning accuracy of the shield tail sealing failure can be improved.

The invention relates to the technical field of rock / soil mass seepage-stress coupling, and discloses a rock-soil mass seepage-stress coupling visualization device and a test method thereof. The rock-soil body seepage-stress coupling visualization device integrates a seepage pressure system controlled by a high-precision plunger pump, a confining pressure and back pressure control system, a loading and measuring device and a visualization observation system composed of a PIV particle image measuring instrument and a three-dimensional XTDIC full-field strain measuring system, and an experiment platform with comprehensive and accurate functions is formed. The device not only can accurately control and measure the seepage pressure, but also can carry out permeability research on the rock / soil body in various stress states, and directly observes and records the seepage field and the structural evolution process in the rock / soil body through an intuitive visual means. The device not only improves the experiment efficiency, but also greatly enhances the intuition and accuracy of research, and provides powerful support for deeply understanding the microscopic and macroscopic behaviors of the rock / soil body under the seepage-stress coupling action.

The invention relates to the field of foundation engineering, and discloses a soil mass critical state-based large open caisson soil sampling control method which comprises the following steps: acquiring soil layer distribution and physical and mechanical parameters of the position of an open caisson, establishing an interaction model of an open caisson blade foot and a soil mass, calculating pressure distribution of a blade foot contact area through a finite element method, and calculating the soil mass critical state of the open caisson. Simulating the distribution condition of a soil body plastic zone and carrying out connectivity analysis; designing an open caisson soil taking construction scheme based on the analysis, wherein the scheme comprises a soil taking sequence, a soil taking depth and a plastic zone proportion index; whether the construction scheme meets the safety and stability requirements of open caisson sinking or not is judged through simulation, if the requirements are not met, soil taking parameters are adjusted, verification is conducted again till the requirements are met, accurate design and dynamic adjustment of the open caisson sinking process are achieved through dual control over the plastic zone proportion index and the connectivity index, and the construction efficiency is improved. And the safety, the stability and the reliability of construction are obviously improved.

The invention discloses a slag permeability coefficient depth distribution prediction method considering a particle crushing effect, and belongs to the technical field of rock-soil body performance prediction. According to the invention, a dynamic triaxial test is carried out on a slag sample, and the dynamic evolution law of grain composition and breakage rate of slag at different depth sites after different vibration times of loading is explored. Meanwhile, a seepage test is carried out on the slag subjected to cyclic loading and crushing through a seepage erosion simulation test device, the critical hydraulic gradient of migration and structural damage of fine particles in the slag of different grades under the seepage erosion effect is explored, the degradation and damage mechanism of the slag is revealed, and a negative index continuous grade formula is used as a hub; according to the method, a prediction model of the particle crushing index and the permeability coefficient is constructed, and the internal mechanism of the particle crushing behavior and the permeability characteristic evolution of the slag roadbed under the cyclic load effect is disclosed, so that the predicted permeability coefficient is closer to the actual permeability coefficient, and the prediction precision is improved.

In a first step, a pretreatment for measuring a moisture characteristic of soil is performed. The pretreatment can be removal of moisture from the soil of interest. For example, removing water that is a cause of a soil mass can be the pretreatment. Next, in a second step, the moisture characteristic of the soil subjected to the pretreatment is measured. The moisture characteristic is a water content of the soil. In addition, the moisture characteristic is a matrix potential value at a specified soil water content. Next, in a third step, the corrosion of the metal member buried in the soil is estimated from the measured moisture characteristic.

The invention relates to the technical field of grouting simulation, in particular to an efficient simulation method and system for grouting at different temperatures based on deep learning, and the method comprises the steps: constructing a relational expression between a rock-soil mass medium and the change of a grouting material under different temperature conditions; the rock-soil mass medium and grouting material change relational expressions under different temperature conditions comprise a relational expression of temperature and porosity, a relational expression of temperature and stress strain, and a relational expression of temperature and slurry viscosity; on the basis of actual stratum data of the grouting area, to-be-determined parameters in all the relational expressions are obtained through fitting; constructing an improved recurrent neural network; training the improved recurrent neural network to obtain a trained improved recurrent neural network; and inputting the temperature of the to-be-predicted grouting area into the trained improved recurrent neural network to obtain the slurry flow velocity and the slurry permeation and diffusion distance of the to-be-predicted grouting area. And efficient simulation of the whole grouting process at different temperatures is realized.

The invention relates to the technical field of geotechnical engineering monitoring, in particular to a soil erosion and particle migration prediction method and system based on acoustic emission monitoring, and the method comprises the following steps: obtaining a soil mass ratio parameter, and preparing a soil sample based on the soil mass ratio parameter to obtain a test soil sample; constructing a multi-field coupling test mechanism to perform a multi-field coupling soil body test on the test soil sample; establishing a soil sample data acquisition device to obtain soil sample monitoring data in the multi-field coupling soil body test process; obtaining acoustic emission characteristic parameters of the test soil body according to the soil sample monitoring data, and establishing a multivariate nonlinear regression model; and constructing a soil body prediction model to realize prediction of soil body erosion and particle migration. Through fusion of multi-field coupling monitoring and machine learning, limitation of a traditional empirical model is broken through, high-precision dynamic prediction of soil erosion and particle migration is realized, a scientific basis is provided for stability evaluation of roadbed engineering, and prediction reliability and engineering applicability are remarkably improved.

The invention provides a landslide probability prediction method and system, computer equipment and a storage medium, and belongs to the field of geological disaster early warning, and the method comprises the steps: obtaining the soil cohesion, internal friction angle and permeability coefficient of rock soil in a landslide region to be predicted; random field generation is carried out on the soil body cohesion, the internal friction angle and the permeability coefficient of the rock soil in the landslide area to be predicted, and soil body cohesion random field data, internal friction angle random field data and permeability coefficient random field data are obtained; carrying out discrete processing on the soil mass cohesion random field data, the internal friction angle random field data and the permeability coefficient random field data to obtain random variables of rock soil in the landslide area to be predicted; inputting the random variables of the rock and soil of the landslide area to be predicted into a pre-trained machine learning model, and calculating and outputting a plurality of slope safety coefficients; and determining the failure probability of the rock soil of the to-be-predicted landslide area according to the plurality of slope safety factor sets. According to the method, soil parameter spatial variability is considered, and the landslide probability prediction accuracy is improved.

The invention provides a field slope stability monitoring method based on acoustic emission, and belongs to the technical field of field slope stability monitoring. In order to solve the technical problems of large soil mass fracture signal attenuation, strong noise interference and poor real-time performance of traditional monitoring in the existing loess slope instability monitoring, the adopted technical scheme is as follows: an inclined hole channel is drilled in the main sliding direction of a slope body by adopting a hydraulic guide drilling machine; vertically inserting the manufactured passive waveguide device from the top surface of the slope top, burying the manufactured active waveguide device into the drilled inclined hole channel, and burying the surface of a slope body by using an in-situ soil body; the acoustic emission probes of the passive waveguide devices and the active waveguide devices are connected with a collection device through signal lines, and the acoustic emission probes send induced acoustic emission signals to the collection device; the acquisition device receives the acoustic emission signals, then preprocesses the acoustic emission signals, extracts time-frequency domain features, and transmits the time-frequency domain features to the cloud system through a wireless network; the method is applied to field slope stability monitoring.

The invention provides a shape function KL expansion random field discretization method considering a slope soil body irregular domain, and belongs to the technical field of soil body parameter random field analysis. Comprising the following steps: establishing a slope numerical model and dividing a discrete grid and a form function grid; establishing a probability distribution model of a soil parameter random field; calculating an element stiffness submatrix ke and an element mass matrix Ee; calculating an autocorrelation matrix rho and a global stiffness matrix B; assembling a global matrix; calculating a characteristic value lambda k, a characteristic function phi k and an expansion term number M; and random field discretization of the slope numerical model is realized. The random field discrete technology provided by the invention is used for efficiently and accurately analyzing the random distribution characteristics of the soil parameters in the rock-soil structure. The discrete random field model can be efficiently constructed in a complex geological structure, the calculation cost is remarkably reduced, the method can be conveniently combined with numerical simulation tools such as a finite element method, and the requirement of actual engineering for efficiency is met while the precision is improved.

The invention provides a method for predicting settlement of a transformer substation in a collapsible loess area based on a neural network, and relates to the technical field of geological engineering monitoring. Then, settlement characteristic indexes such as collapsibility, bearing capacity influence and deformation stability are obtained through analysis, a prediction model is established with soil mass mechanical data as input and the settlement characteristic indexes as output, the model performance is optimized through a particle swarm optimization algorithm and a loss function, and finally a fitness function is constructed according to the settlement characteristic indexes. And calculating the settlement fitness value of each sub-region, evaluating the settlement amount in combination with load time sequence data, setting a settlement threshold value, and carrying out risk marking on the sub-regions exceeding the threshold value. The settlement risk of the loess area where the transformer substation is located is effectively evaluated and controlled by establishing the settlement characteristic index prediction model and the dynamic monitoring mechanism.

The invention provides a soil moisture content detection method based on unsteady heat conduction and optical fiber temperature measurement, which comprises the following steps: heating a soil body in a target measurement area based on an active heating method, and measuring the temperature value of the soil body at each moment under different radial distances from a heating source in the heating process; substituting the soil body temperature value at any moment in the heating process and the corresponding radial distance into a predetermined soil body moisture content relation model to obtain the soil body moisture content at the position corresponding to the radial distance from the heating source in the target measurement area at the corresponding moment; and determining the soil mass moisture content of the target measurement area according to the soil mass moisture content at each radial distance position from the heating source in the target measurement area at the corresponding moment. According to the method, the relationship between the soil moisture content and the soil temperature value is established, and in-situ monitoring and long-time monitoring of the large-range soil in the target measuring area are achieved through the soil temperature value obtained through the active heating method.

The invention belongs to the technical field of road slope monitoring, and discloses a multi-source information fusion road slope comprehensive monitoring and early warning system, which comprises the following steps: acquiring slope geometric data and soil mass data; obtaining soil body properties based on the constructed soil body viscosity prediction model; the method comprises the following steps: carrying out block division on a side slope to obtain side slope blocks, carrying out stability calculation on the side slope blocks to obtain a stability coefficient, constructing a minimum stability coefficient objective function based on the stability coefficient and determining a minimum division scheme of the stability coefficient, and carrying out block aggregation on the minimum division scheme of the stability coefficient through a clustering algorithm to obtain # imgabs0 edge block clusters; performing safety analysis on the edge block cluster to obtain a safe area and a dangerous area; constructing a stability prediction model based on the safety area, and performing future safety analysis on the safety area through a prediction result of the stability prediction model; the accuracy and timeliness of slope monitoring are greatly improved.

The invention provides a tubular pile vertical dynamic stiffness determination method and system, and relates to the technical field of dynamic stiffness determination, and the method specifically comprises the following steps: collecting material characteristics, geometric characteristics and soil mass parameters of a tubular pile; performing a dynamic load test on the tubular pile to obtain dynamic response data of the tubular pile, and generating a dynamic response index; the pipe pile material characteristics and the geometric characteristics are combined to generate a first influence index; generating a second influence index based on the soil parameter; and synthesizing the first influence index, the second influence index and the dynamic response index to generate a calculation expression of the vertical dynamic stiffness of the tubular pile. According to the method, the material characteristics, geometric characteristics and soil parameters of the tubular pile are collected and analyzed in detail, so that the design precision is improved, and the bearing capacity and safety of the tubular pile are enhanced. And secondly, inherent frequency and damping ratio data provided by the dynamic load test enable the understanding of the dynamic characteristics of the tubular pile to be deeper, and the risk of structural damage is reduced.

The invention discloses a coal mine slope stability analysis method based on numerical simulation. The coal mine slope stability analysis method comprises the following steps: acquiring strength and permeability data of a rock-soil body through a field investigation point location, processing by adopting a statistical analysis method, obtaining initial parameter statistical characteristics, simulating parameter random distribution of the rock-soil body in a three-dimensional space, and obtaining a heterogeneous parameter distribution field; a finite element analysis method is adopted to calculate stress-strain response of the slope under external load and hydrological conditions, a local stress concentration area is determined, and a slope stability index is obtained; acquiring a local deviation value of a corresponding parameter distribution field for an area where the slope stability index exceeds the range, adjusting the deviation value through an iterative algorithm, and determining an optimized parameter distribution field; and performing finite element analysis again based on the optimized parameter distribution field, judging distribution positions of potential instability points, and determining a final risk boundary according to the distribution positions of the potential instability points. According to the method, the scientificity and reliability of slope stability evaluation are improved.

The invention provides an existing building deformation risk assessment method and device which can be applied to the technical field of tunnel engineering and building engineering. The evaluation method comprises the following steps: acquiring tunnel data, and soil mass data and settlement range data corresponding to a new tunnel; inputting the tunnel data, the soil mass data and the settlement range data into a prediction model to obtain settlement results corresponding to the plurality of measuring points; and determining a risk assessment result of the to-be-assessed building based on the settlement result, the to-be-assessed building data and the settlement range data. The prediction model is obtained by training the following operations: constructing an initial prediction model by using sample tunnel data, sample soil body data, sample measuring point data and a plurality of initial parameters; updating the plurality of initial parameters based on the plurality of updating strategies to obtain a plurality of target parameters; and updating the initial prediction model by using the plurality of target parameters to obtain a prediction model. According to the method, the accuracy of a building risk assessment result can be improved, and the consumption of system resources is reduced.

The invention relates to the technical field of geotechnical engineering, in particular to a shearing and stretching method and device between a high polymer and a soil mass, the shearing and stretching device comprises a placing frame, two shearing mold fixing pieces and two stretching mold fixing pieces, the two shearing loading mechanism fixing pieces are connected with a shearing loading mechanism through two first fixing screws, and the two stretching mold fixing pieces are connected with a stretching mold through two second fixing screws. The two stretching loading mechanism fixing pieces are connected with the stretching loading mechanism through two second fixing screws, the placing frame is arranged on the two shearing mold fixing pieces, the placing frame is used for placing a test piece, and the placing frame is also matched with the two stretching loading mechanism fixing pieces; in this way, the technical problems that in the prior art, a shearing and stretching method device is limited in fixing effect, poor in adaptability, complex in operation and lack of real-time analysis capacity are solved.

The invention relates to the technical field of geological disaster risk research, in particular to a landslide risk evaluation method and system based on a substation failure model. Carrying out detailed investigation on the landslide of the transformer substation to obtain physical and mechanical properties of a rock-soil body; calculating seepage characteristics of the rock-soil body by using a rainfall infiltration hydrograph model, simulating landslide stability under different rainfall working conditions by using FLAC3D software, and calculating an annual instability probability in combination with a Monte Carlo method; and simulating deformation and failure models of various facilities in the transformer substation in the landslide instability process by using FLAC3D, carrying out valuing on the vulnerability of various facilities, and calculating the economic loss of the transformer substation under various working conditions. The invention further comprises corresponding system implementation. According to the method, comprehensive, quantitative and accurate assessment of the landslide risk of the transformer substation is realized by integrating geological survey, a hydrological model, numerical simulation and a statistical method, a scientific basis is provided for safety management of a power grid in a mountainous area, and the method can be popularized and applied to risk assessment of other similar geological disasters.

The invention discloses a method for inverting field scale debris flow through earth sound signals, and the method comprises the following steps: S1, constructing a conversion relation between debris flow earth sound signals and vibration signals, converting the physical work of a rock-soil body into signal work, and constructing a theoretical relation between the signal amplitude epsilon'of an FBG sensor and the single compression work W of the rock-soil body; and S2, on the basis of the theoretical basis of the step S1, constructing a physical model for inverting the debris flow. According to the method, inverse operation of Fch-kinetic parameters can be completed, an inversion chain of'earth sound signals-Fch-kinetic parameters' is formed, and a physical model of earth sound inversion debris flow is successfully constructed.

A stratum reinforcement modeling and analysis method for a shield tunnel crossing an existing structure is provided. Geological information and an engineering structure condition of the existing structure are acquired. Physical parameters of different soil mass layers are determined based on a laboratory test. A three-dimensional (3D) model is constructed. Mesh generation is performed on the 3D model defining a constraint for the 3D model. Model parameters are selected for the 3D model. A soil mass constitutive model is selected for the 3D model. Synchronous grouting simulation, construction load simulation and shield tunneling construction simulation are performed on the 3D model. Stratum parameters are changed to achieve stratum reinforcement modeling. Data analysis is performed by adopting different reinforcement schemes to achieve stratum reinforcement modeling and numerical analysis of the process of the shield tunnel crossing the existing structure.

The invention relates to the field of geotechnical engineering, and discloses a portable intelligent measuring device and method for the optimal moisture content and the maximum dry density of a soil mass, and the device comprises an automatic sample preparation system integrating stirring, heating and water adding functions, a similar compaction system based on static pressure and frictional resistance measurement, and an intelligent control system, the detachable inner barrel is used as a connecting core; the method comprises the following steps: automatically preparing a series of to-be-detected soil samples with different water contents, performing class compaction on each soil sample to measure corresponding interface friction resistance, and finally calling a conversion model by an intelligent system, and calculating and outputting the optimal water content and the maximum dry density. According to the invention, automatic sample preparation, indirect measurement and intelligent analysis are modularly integrated, so that a traditional compaction test is converted into an automatic test process which can be quickly and accurately completed on an engineering site, and the problems that the test period is long, the test depends on a laboratory, and site construction cannot be timely guided in the prior art are solved.